​Assurance in Vibe Coding Days

​AI coding tools have changed how quickly developers can turn ideas into working software. But generating code is only one part of building software that can be trusted.

​How do we move from AI-generated code to software we can confidently deliver?

​This session examines the engineering practices that help teams maintain quality, reliability, and control when building software through vibe coding.

​We will look beyond the speed of code generation to the work that makes delivery dependable: validating AI-generated code, testing assumptions, identifying failure modes, reviewing implementation decisions, and ensuring the final output meets the intended requirements.

​The focus is on the gap between code that works in a demo and software that is ready for delivery.

​What you'll take away

• ​A practical approach to validating AI-generated code.

• ​Ways to identify defects, edge cases, and hidden assumptions before delivery.

• ​The role of testing, code review, and verification in AI-assisted development.

• ​Engineering practices that balance development speed with software quality.

• ​A clearer understanding of where human judgement remains essential in the development lifecycle.

​Who should attend?

​Software engineers, AI engineers, Data engineers, AI Architects, Data analysts, LLM engineer technical leads, and practitioners using AI coding tools who want to make their development process more reliable.

​The Data & AI Guild · Hyderabad

​A practitioner-led space for honest conversations about what works, what fails, and what the field needs to figure out next.

​Date: 14 October 2026
Venue: Sparity, Hyderabad
Sponsor: Sparity

​Register to join the conversation.